Utilization of Thromboelastography with Platelet Mapping to Predict Infection and Poor Wound Healing in Postoperative Vascular Patients.


Journal

Annals of vascular surgery
ISSN: 1615-5947
Titre abrégé: Ann Vasc Surg
Pays: Netherlands
ID NLM: 8703941

Informations de publication

Date de publication:
Nov 2022
Historique:
received: 28 02 2022
revised: 13 03 2022
accepted: 14 03 2022
pubmed: 28 3 2022
medline: 25 2 2023
entrez: 27 3 2022
Statut: ppublish

Résumé

Postoperative infection and wound dehiscence rates are higher than expected in peripheral artery disease and contribute significantly to limb loss and mortality. Microvascular pathology characterized by microthrombi and increased platelet aggregation have been cited as contributing factors to poor wound healing and infection. The emergence of viscoelastic assays, such as thromboelastography with platelet mapping (TEG-PM), have been utilized to identify prothrombotic states and may provide insight into a patient's microvascular coagulation profile. This prospective, observational study aimed to determine if TEG-PM could predict poor wound healing or infection following lower extremity revascularization. All patients undergoing revascularization between December 2020 and January 2022 were prospectively included and followed for wound complications or non-surgical site infections of the index limb. TEG-PM metrics at the first postoperative follow-up in the nonevent group was compared to the TEG-PM sample preceding the diagnosis of infection/dehiscence in the event group. Cox proportional hazards (PH) regression was used to model the predictive value of viscoelastic parameters. Cut-point analysis to determine high-risk groups was determined by performing receiver operating characteristic curve analysis. Of the 102 patients, 18.6% experienced infection/dehiscence. The TEG-PM sample analyzed in the event group was, on average, 19.5 days prior to the diagnosis of an event. The event group had significantly higher maximum clot amplitude (MA) (47.3 mm ± 16.0 vs. 30.6 mm ± 15.3, P < 0.01), higher platelet aggregation (71.3% ± 27.7 vs. 31.2% ± 24.0, P < 0.01), and lower platelet inhibition (28.7% ± 27.7 vs. 68.7% ± 24.1, P < 0.01). Cox PH analysis identified platelet aggregation as an independent and consistent predictor of infection (hazard ratio = 1.04, 95% confidence interval 1.03-1.06, P < 0.01). An optimal cut-point of > 33.2 mm MA, > 46.6% platelet aggregation, or < 55.8% platelet inhibition identifies those with infection/dehiscence with 79.0-89.5% sensitivity. These are the first data to provide a quantitative link between prothrombotic viscoelastic coagulation profiles with the development of infection/dehiscence. Based on the cut-points of > 33.2 mm MA, > 46.6% platelet aggregation, or < 55.8% platelet inhibition, we recommend consideration of an enhanced antimicrobial or antithrombotic approach for these high risk groups.

Sections du résumé

BACKGROUND BACKGROUND
Postoperative infection and wound dehiscence rates are higher than expected in peripheral artery disease and contribute significantly to limb loss and mortality. Microvascular pathology characterized by microthrombi and increased platelet aggregation have been cited as contributing factors to poor wound healing and infection. The emergence of viscoelastic assays, such as thromboelastography with platelet mapping (TEG-PM), have been utilized to identify prothrombotic states and may provide insight into a patient's microvascular coagulation profile. This prospective, observational study aimed to determine if TEG-PM could predict poor wound healing or infection following lower extremity revascularization.
METHODS METHODS
All patients undergoing revascularization between December 2020 and January 2022 were prospectively included and followed for wound complications or non-surgical site infections of the index limb. TEG-PM metrics at the first postoperative follow-up in the nonevent group was compared to the TEG-PM sample preceding the diagnosis of infection/dehiscence in the event group. Cox proportional hazards (PH) regression was used to model the predictive value of viscoelastic parameters. Cut-point analysis to determine high-risk groups was determined by performing receiver operating characteristic curve analysis.
RESULTS RESULTS
Of the 102 patients, 18.6% experienced infection/dehiscence. The TEG-PM sample analyzed in the event group was, on average, 19.5 days prior to the diagnosis of an event. The event group had significantly higher maximum clot amplitude (MA) (47.3 mm ± 16.0 vs. 30.6 mm ± 15.3, P < 0.01), higher platelet aggregation (71.3% ± 27.7 vs. 31.2% ± 24.0, P < 0.01), and lower platelet inhibition (28.7% ± 27.7 vs. 68.7% ± 24.1, P < 0.01). Cox PH analysis identified platelet aggregation as an independent and consistent predictor of infection (hazard ratio = 1.04, 95% confidence interval 1.03-1.06, P < 0.01). An optimal cut-point of > 33.2 mm MA, > 46.6% platelet aggregation, or < 55.8% platelet inhibition identifies those with infection/dehiscence with 79.0-89.5% sensitivity.
CONCLUSIONS CONCLUSIONS
These are the first data to provide a quantitative link between prothrombotic viscoelastic coagulation profiles with the development of infection/dehiscence. Based on the cut-points of > 33.2 mm MA, > 46.6% platelet aggregation, or < 55.8% platelet inhibition, we recommend consideration of an enhanced antimicrobial or antithrombotic approach for these high risk groups.

Identifiants

pubmed: 35339591
pii: S0890-5096(22)00137-6
doi: 10.1016/j.avsg.2022.03.008
pii:
doi:

Types de publication

Observational Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

213-224

Informations de copyright

Copyright © 2022 Elsevier Inc. All rights reserved.

Auteurs

Monica Majumdar (M)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Srihari Lella (S)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Ryan P Hall (RP)

Department of Surgery, Tufts Medical Center/Tufts University School of Medicine, Boston, MA.

Natalie Sumetsky (N)

Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA.

Harold D Waller (HD)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Imani McElroy (I)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Brandon Sumpio (B)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Zach M Feldman (ZM)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Young Kim (Y)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Charles DeCarlo (C)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Mary Warner (M)

Department of Surgery, Tufts Medical Center/Tufts University School of Medicine, Boston, MA.

Kathryn Nuzzolo (K)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Amanda Kirshkaln (A)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA.

Anahita Dua (A)

Division of Vascular and Endovascular Surgery, Massachusetts General Hospital/Harvard Medical School, Boston, MA. Electronic address: adua1@mgh.harvard.edu.

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